100+ datasets found
  1. Demographics API - By Geography Type and Geography ID

    • datasets.ai
    • catalog.data.gov
    • +2more
    23
    Updated Sep 4, 2024
    + more versions
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    Department of Commerce (2024). Demographics API - By Geography Type and Geography ID [Dataset]. https://datasets.ai/datasets/demographics-api-by-geography-type-and-geography-id
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    23Available download formats
    Dataset updated
    Sep 4, 2024
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    Authors
    Department of Commerce
    Description

    This API returns a search for the demographic information for a particular geography type and geography ID

  2. Demographic by Race 2021 (all geographies, statewide)

    • hub.arcgis.com
    • opendata.atlantaregional.com
    • +1more
    Updated Mar 10, 2023
    + more versions
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    Georgia Association of Regional Commissions (2023). Demographic by Race 2021 (all geographies, statewide) [Dataset]. https://hub.arcgis.com/maps/b1651445db7a419794f1dc107968d885
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    Dataset updated
    Mar 10, 2023
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

  3. a

    Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy

    • hub.arcgis.com
    • africageoportal.com
    Updated Aug 20, 2020
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    Africa GeoPortal (2020). Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy [Dataset]. https://hub.arcgis.com/maps/ffd1b8a7ffbf4b758fc15dcc0a6060c3
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    Dataset updated
    Aug 20, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    (by Joseph Kerski)This map is for use in the "What is the spatial pattern of demographic variables around the world?" activity in Section 1 of the Going Places with Spatial Analysiscourse. The map contains population characteristics by country for 2013.These data come from the Population Reference Bureau's 2014 World Population Data Sheet.The Population Reference Bureau (PRB) informs people around the world about population, health, and the environment, empowering them to use that information to advance the well-being of current and future generations.PRB analyzes complex demographic data and research to provide the most objective, accurate, and up-to-date population information in a format that is easily understood by advocates, journalists, and decision makers alike.The 2014 year's data sheet has detailed information on 16 population, health, and environment indicators for more than 200 countries. For infant mortality, total fertility rate, and life expectancy, we have included data from 1970 and 2013 to show change over time. This year's special data column is on carbon emissions.For more information about how PRB compiles its data, see: https://www.prb.org/

  4. V

    2019 US Census All Counties & County Equivalents

    • data.virginia.gov
    geojson
    Updated Nov 22, 2024
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    Other (2024). 2019 US Census All Counties & County Equivalents [Dataset]. https://data.virginia.gov/dataset/2019-us-census-all-counties-county-equivalents
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    geojson(224806786)Available download formats
    Dataset updated
    Nov 22, 2024
    Dataset authored and provided by
    Other
    Area covered
    United States
    Description

    2019 US Census All Counties and County Equivalents geospatial data

    U.S. Census Bureau; TIGER/Line Shapefiles 2019 Data accessed from: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2019.html

    TIGER/Line Shapefiles do not include demographic data, but they do contain geographic entity codes (GEOIDs) that can be linked to the Census Bureau’s demographic data.

    The Geographic Areas Reference Manual (GARM) describes in great detail the basic geographic entities the Census Bureau uses (https://www.census.gov/programs-surveys/acs/geography-acs.html).

    TIGER Data Products Guide (https://www.census.gov/programs-surveys/geography/guidance/tiger-data-products-guide.html)

  5. a

    Population Density in the US 2020 Census

    • hub.arcgis.com
    • data-bgky.hub.arcgis.com
    Updated Jun 20, 2024
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    University of South Florida GIS (2024). Population Density in the US 2020 Census [Dataset]. https://hub.arcgis.com/maps/58e4ee07a0e24e28949903511506a8e4
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    Dataset updated
    Jun 20, 2024
    Dataset authored and provided by
    University of South Florida GIS
    Area covered
    Description

    This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

  6. 10 powerful tools and maps with which to teach about population and...

    • library.ncge.org
    Updated Jul 27, 2021
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    NCGE (2021). 10 powerful tools and maps with which to teach about population and demographics [Dataset]. https://library.ncge.org/documents/bae1d5f1cba243ea88d09b043b8444ee
    Explore at:
    Dataset updated
    Jul 27, 2021
    Dataset provided by
    National Council for Geographic Educationhttp://www.ncge.org/
    Authors
    NCGE
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

  7. Demographic change 2010 - 2023 (all geographies, statewide)

    • gisdata.fultoncountyga.gov
    • opendata.atlantaregional.com
    Updated Feb 21, 2025
    + more versions
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    Georgia Association of Regional Commissions (2025). Demographic change 2010 - 2023 (all geographies, statewide) [Dataset]. https://gisdata.fultoncountyga.gov/maps/f70f4d7defb94a20987e59061b012bbe
    Explore at:
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics Department at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.For a deep dive into the data model including every specific metric, see the ACS 2019-2023. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e23Estimate from 2019-23 ACS_m23Margin of Error from 2019-23 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_23Change, 2010-23 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)CCDIST = County Commission Districts (statewide where applicable)CCSUPERDIST = County Commission Superdistricts (DeKalb)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2019-2023). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2019-2023Open Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/182e6fcf8201449086b95adf39471831/about

  8. USA Demographics - Human Geography GeoInquiries 2020

    • geoinquiries-education.hub.arcgis.com
    • hub.arcgis.com
    Updated Aug 23, 2018
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    Esri GIS Education (2018). USA Demographics - Human Geography GeoInquiries 2020 [Dataset]. https://geoinquiries-education.hub.arcgis.com/maps/570fdb49796243bd8a05fc6e1df4c417
    Explore at:
    Dataset updated
    Aug 23, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri GIS Education
    Area covered
    Description

    This map is for human geography classrooms and tied to the AP benchmarks. Learn more about GeoInquiries at www.esri.com/geoinquiries

  9. D

    SFDPH reporting - geography population estimates

    • data.sfgov.org
    csv, xlsx, xml
    Updated Mar 27, 2025
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    American Community Survey (2025). SFDPH reporting - geography population estimates [Dataset]. https://data.sfgov.org/w/35v5-seg9/ikek-yizv?cur=vUmhQtB0oWV&from=root
    Explore at:
    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Mar 27, 2025
    Dataset authored and provided by
    American Community Survey
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    This filtered view contains the population estimates for San Francisco geographic units from the U.S. Census Bureau’s American Community Survey that are used in the Department of Public Health’s public reporting. Details on the underlying geographic unit data from the American Community Survey are available below. The geographies included are census tracts, analysis neighborhoods, and zip codes (ZCTA). We are using 2016-2020 ACS estimates in our public reporting, but additional years are included in this view as well for historical purposes.

    The COVID-19 reports which use this data are available on SF.gov by clicking here.

    San Francisco Population and Demographic Census data dataset filtered on:

    • "geography" =
      • 'neighborhood'
      • OR 'tract'
      • OR 'zcta'
    • AND "demographic_category" = 'all'
    A. SUMMARY This dataset contains population and demographic estimates and associated margins of error obtained and derived from the US Census. The data is presented over multiple years and geographies. The data is sourced primarily from the American Community Survey.

    B. HOW THE DATASET IS CREATED The raw data is obtained from the census API. Some estimates as published as-is and some are derived.

    C. UPDATE PROCESS New estimates and years of data are appended to this dataset. To request additional census data for San Francisco, email support@datasf.org

    D. HOW TO USE THIS DATASET The dataset is long and contains multiple estimates, years and geographies. To use this dataset, you can filter by the overall segment which contains information about the source, years, geography, demographic category and reporting segment. For census data used in specific reports, you can filter to the reporting segment. To use a subset of the data, you can create a filtered view. More information of how to filter data and create a view can be found here

  10. n

    04 - USA demographics - Esri GeoInquiries collection for Human Geography

    • library.ncge.org
    • geoinquiries-education.hub.arcgis.com
    Updated Jun 8, 2020
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    NCGE (2020). 04 - USA demographics - Esri GeoInquiries collection for Human Geography [Dataset]. https://library.ncge.org/documents/815b27221bec4f498bb4310edce6ded1
    Explore at:
    Dataset updated
    Jun 8, 2020
    Dataset authored and provided by
    NCGE
    Description

    Students will explore U.S. census data to see the spatial differences in the United States’ population. The activity uses a web-based map and is tied to the AP Human Geography benchmarks. Learning outcomes:· Unit 2, A1: Geographical analysis of population (density, distribute and scale)· Unit 2, A3: Geographical analysis of population (composition: age, sex, income, education and ethnicity)· Unit 2, A4: Geographical analysis of population (patterns of fertility, mortality and health)Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries

  11. Demographic 2020 (DHC, all geographies, statewide)

    • gisdata.fultoncountyga.gov
    • hub.arcgis.com
    Updated Mar 28, 2024
    + more versions
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    Georgia Association of Regional Commissions (2024). Demographic 2020 (DHC, all geographies, statewide) [Dataset]. https://gisdata.fultoncountyga.gov/maps/32c2c56a3bfd4e63a2e669ca869096b3
    Explore at:
    Dataset updated
    Mar 28, 2024
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.For a deep dive into the data model including every specific metric, see the DHC 2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find geography definitions and user notes below.These are indicators built from the 2020 Decennial CensusThis is the second release based on the 2020 Census following the Redistricting Data release previously. The DHC release lets us drill deeper on age than the redistricting data (that only breaks at 0-17 and 18+). Additionally, we get some data on household type and housing tenure.Geographies AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage) ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit) ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit) BeltLineStatistical (buffer) BeltLineStatisticalSub (subareas) Census Tract (statewide) CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit) City (statewide) City of Atlanta Council Districts (City of Atlanta) City of Atlanta Neighborhood Planning Unit (City of Atlanta) City of Atlanta Neighborhood Statistical Areas (City of Atlanta) County (statewide) Georgia House (statewide) Georgia Senate (statewide) HSSA = High School Statistical Area (11 county region) MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit) Regional Commissions (statewide) State of Georgia (single geographic unit) Superdistrict (ARC region) US Congress (statewide) UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit) ZIP Code Tabulation Areas (statewide)Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2020Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/GARC::data-manifest-for-arc-census-demographic-and-housing-characteristics-dhc-2020-release/aboutFor more information, visit the US Census DHC Technical Documentation webpage.

  12. V

    2019 Virginia Census Tracts

    • data.virginia.gov
    csv
    Updated Nov 22, 2024
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    Office of INTERMODAL Planning and Investment (2024). 2019 Virginia Census Tracts [Dataset]. https://data.virginia.gov/dataset/2019-virginia-census-tracts
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 22, 2024
    Dataset authored and provided by
    Office of INTERMODAL Planning and Investment
    Description

    2019 Virginia Census Tracts geospatial data

    U.S. Census Bureau; TIGER/Line Shapefiles 2019 Data accessed from: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2019.html

    TIGER/Line Shapefiles do not include demographic data, but they do contain geographic entity codes (GEOIDs) that can be linked to the Census Bureau’s demographic data.

    The Geographic Areas Reference Manual (GARM) describes in great detail the basic geographic entities the Census Bureau uses (https://www.census.gov/programs-surveys/acs/geography-acs.html).

    TIGER Data Products Guide (https://www.census.gov/programs-surveys/geography/guidance/tiger-data-products-guide.html)

  13. Demographic by Race 2023 (all geographies, statewide)

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    Updated Feb 21, 2025
    + more versions
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    Georgia Association of Regional Commissions (2025). Demographic by Race 2023 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/5d3ef7696cf1440faad2d512c3d10297
    Explore at:
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics Department at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.For a deep dive into the data model including every specific metric, see the ACS 2019-2023. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e23Estimate from 2019-23 ACS_m23Margin of Error from 2019-23 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_23Change, 2010-23 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)CCDIST = County Commission Districts (statewide where applicable)CCSUPERDIST = County Commission Superdistricts (DeKalb)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2019-2023). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2019-2023Open Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/182e6fcf8201449086b95adf39471831/about

  14. g

    GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business...

    • datastore.gapmaps.com
    Updated Aug 14, 2024
    + more versions
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    GapMaps (2024). GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business Decisions | Consumer Spending Data| Demographic Data [Dataset]. https://datastore.gapmaps.com/products/gapmaps-premium-demographic-data-by-ags-usa-canada-gis-gapmaps
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    Dataset updated
    Aug 14, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Canada, United States
    Description

    GapMaps GIS Data sourced from Applied Geographic Solutions includes over 40k Demographic variables across topics including estimates & projections on population, demographics, neighborhood segmentation, consumer spending, crime index & environmental risk available at census block level.

  15. H

    Vote Choice and Population Size by Geography, Demographics, and Turnout

    • dataverse.harvard.edu
    Updated May 2, 2023
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    Shiro Kuriwaki; Stephen Ansolabehere; Angelo Dagonel; Soichiro Yamauchi (2023). Vote Choice and Population Size by Geography, Demographics, and Turnout [Dataset]. http://doi.org/10.7910/DVN/MAZNJ6
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 2, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Shiro Kuriwaki; Stephen Ansolabehere; Angelo Dagonel; Soichiro Yamauchi
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Dataset funded by
    NSF
    Description

    Modeled vote choice of geographic, demographic, and turnout subgroups with survey and ecological data in the US. The current version models Presidential vote choice in 2016 and 2020 for each contemporaneous congressional district and each of four racial groups. The methodology is introduced and explained in Kuriwaki et al. (2023). “The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level.” American Political Science Review. https://osf.io/mk9e6/

  16. u

    Income Status (4A) and Selected Geographic, Demographic, Family, Income,...

    • data.urbandatacentre.ca
    Updated Sep 30, 2024
    + more versions
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    (2024). Income Status (4A) and Selected Geographic, Demographic, Family, Income, Educational, Cultural, Language and Labour Force Characteristics of Unattached Individuals (197) for Unattached Individuals 15 Years and Over in Private Households, for Canada and Provinces, 1995 and 2000 - 20% Sample Data - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-fc9a6a17-cf0a-4514-901f-95ad1f19fad7
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    Dataset updated
    Sep 30, 2024
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

  17. n

    Geographic Regions

    • demography.osbm.nc.gov
    • linc.osbm.nc.gov
    • +3more
    csv, excel, geojson +1
    Updated Mar 19, 2021
    + more versions
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    (2021). Geographic Regions [Dataset]. https://demography.osbm.nc.gov/explore/dataset/north-carolina-geographic-regions/
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    geojson, json, excel, csvAvailable download formats
    Dataset updated
    Mar 19, 2021
    Description

    Provides regional identifiers for county based regions of various types. These can be combined with other datasets for visualization, mapping, analyses, and aggregation. These regions include:Metropolitan Statistical Areas (Current): MSAs as defined by US OMB in 2023Metropolitan Statistical Areas (2010s): MSAs as defined by US OMB in 2013Metropolitan Statistical Areas (2000s): MSAs as defined by US OMB in 2003Region: Three broad regions in North Carolina (Eastern, Western, Central)Council of GovernmentsProsperity Zones: NC Department of Commerce Prosperity ZonesNCDOT Divisions: NC Dept. of Transportation DivisionsNCDOT Districts (within Divisions)Metro Regions: Identifies Triangle, Triad, Charlotte, All Other Metros, & Non-MetropolitanUrban/Rural defined by:NC Rural Center (Urban, Regional/Suburban, Rural) - 2020 Census designations2010 Census (Urban = Counties with 50% or more population living in urban areas in 2010)2010 Census Urbanized (Urban = Counties with 50% or more of the population living in urbanized areas in 2010 (50,000+ sized urban area))Municipal Population - State Demographer (Urban = counties with 50% or more of the population living in a municipality as of July 1, 2019)Isserman Urban-Rural Density Typology

  18. Demographic by Race 2022 (all geographies, statewide)

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • opendata.atlantaregional.com
    • +1more
    Updated Mar 1, 2024
    + more versions
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    Georgia Association of Regional Commissions (2024). Demographic by Race 2022 (all geographies, statewide) [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/449b09ed0cd046078e8a3e7d7327b1bb
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. .
    For a deep dive into the data model including every specific metric, see the ACS 2018-2022 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e22Estimate from 2018-22 ACS_m22Margin of Error from 2018-22 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_22Change, 2010-22 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2018-2022). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2018-2022Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/3b86ee614e614199ba66a3ff1ebfe3b5/about

  19. Race & Ethnicity 2022 (all geographies, statewide)

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +2more
    Updated Mar 1, 2024
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    Georgia Association of Regional Commissions (2024). Race & Ethnicity 2022 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/b57e042f1c9e49c887d3bb048dd56daa
    Explore at:
    Dataset updated
    Mar 1, 2024
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. .
    For a deep dive into the data model including every specific metric, see the ACS 2018-2022 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e22Estimate from 2018-22 ACS_m22Margin of Error from 2018-22 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_22Change, 2010-22 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2018-2022). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2018-2022Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/3b86ee614e614199ba66a3ff1ebfe3b5/about

  20. d

    Statistics Korea_SGIS Open Platform_Demographics

    • data.go.kr
    json
    Updated Sep 20, 2024
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    (2024). Statistics Korea_SGIS Open Platform_Demographics [Dataset]. https://www.data.go.kr/en/data/15088190/openapi.do
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 20, 2024
    License

    https://data.go.kr/ugs/selectPortalPolicyView.dohttps://data.go.kr/ugs/selectPortalPolicyView.do

    Description

    Demographic data reconstructed from the Population and Housing Census of the National Statistical Office for population-related statistics according to conditions to fit the SGIS open platform

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Department of Commerce (2024). Demographics API - By Geography Type and Geography ID [Dataset]. https://datasets.ai/datasets/demographics-api-by-geography-type-and-geography-id
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Demographics API - By Geography Type and Geography ID

Explore at:
23Available download formats
Dataset updated
Sep 4, 2024
Dataset provided by
United States Department of Commercehttp://commerce.gov/
Authors
Department of Commerce
Description

This API returns a search for the demographic information for a particular geography type and geography ID

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